This paper illustrates a simple idea on how to interpret undecompsable generalized multiplicative modules of linear logic as probabilistic methods of a logic prgramming language. These new modules/methods allow to express kinds of propagation of probability distribution inside Bayesian Networks that cannot be expressed by standard Prolog-like programming languages.